pcr <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/pcr.csv")
dim(pcr)
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)
# explore using product of housekeeping genes to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL X RPS", ylab="Tbet Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL X RPS", ylab="CD25 Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL X RPS", ylab="FOXP3 Ct")#
abline(v=600,lty=3)
# read in document containing reference back to sample ID#
rna_id <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/rna_isolation.csv")#
rpl <- subset(pcr, GENE == "RPL41")#
rps <- subset(pcr, GENE == "RPS9")#
index1 <- match(rpl$SAMPLEID, rna_id$STORED.IN.TUBE)#
#
quartz(,8,4); layout(matrix(c(1,2),1,2))#
plot(rps$Ct, rna_id$PURITY[index1],xlim=c(15,35), xlab="Ct")#
points(rpl$Ct, rna_id$PURITY[index1],col=3)#
legend("topright", c("rps", "rpl"), pch=19,col=c(1,3))#
plot(rps$Ct, rna_id$CONCENTRATION[index1],xlim=c(15,35), ylim=c(0,50), xlab="Ct")#
points(rpl$Ct, rna_id$CONCENTRATION[index1],col=3)
# explore using only RPL41 to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL", ylab="Tbet Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL", ylab="CD25 Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL", ylab="FOXP3 Ct")#
abline(v=25,lty=3)
# use this to filter#
#
rpl <- subset(rpl, Ct <25)#
#
# ONLY THE TUBE ID'S FOR WHICH THE RPL41 CT WAS <25 WILL BE INCLUDED IN FURTHER ANALYSES#
#
index2 <- pcr$SAMPLEID %in% rpl$SAMPLEID#
#
pcr <- data.frame(SAMPLEID = pcr$SAMPLEID[index2], GENE = pcr$GENE[index2], Ct = pcr$Ct[index2], Exp = pcr$Exp[index2], stim = NA)#
#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# now need to work on analyses by stim, patient, visit#
#
i <- grep("MC", rna_id$STIMULANT)#
MC <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MC] <- "MED_CTRL"#
#
i <- grep("MM", rna_id$STIMULANT)#
MM <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MM] <- "MUS_M1"#
#
i <- grep("TT", rna_id$STIMULANT)#
TT <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[TT] <- "TT"#
#
#
# need to calculate ddCt values by tube -- probably need to create loops
rpl <- subset(pcr, GENE == "RPL41")#
rps <- subset(pcr, GENE == "RPS9")#
index1 <- match(rpl$SAMPLEID, rna_id$STORED.IN.TUBE)#
#
quartz(,8,4); layout(matrix(c(1,2),1,2))#
plot(rps$Ct, rna_id$PURITY[index1],xlim=c(15,35), xlab="Ct")#
points(rpl$Ct, rna_id$PURITY[index1],col=3)#
legend("topright", c("rps", "rpl"), pch=19,col=c(1,3))#
plot(rps$Ct, rna_id$CONCENTRATION[index1],xlim=c(15,35), ylim=c(0,50), xlab="Ct")#
points(rpl$Ct, rna_id$CONCENTRATION[index1],col=3)#
#
#
# explore using only RPL41 to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL", ylab="Tbet Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL", ylab="CD25 Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL", ylab="FOXP3 Ct")#
abline(v=25,lty=3)#
#
# use this to filter#
#
rpl <- subset(rpl, Ct <30)#
#
# ONLY THE TUBE ID'S FOR WHICH THE RPL41 CT WAS <30 WILL BE INCLUDED IN FURTHER ANALYSES#
#
index2 <- pcr$SAMPLEID %in% rpl$SAMPLEID#
#
pcr <- data.frame(SAMPLEID = pcr$SAMPLEID[index2], GENE = pcr$GENE[index2], Ct = pcr$Ct[index2], Exp = pcr$Exp[index2], stim = NA)#
#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# now need to work on analyses by stim, patient, visit#
#
i <- grep("MC", rna_id$STIMULANT)#
MC <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MC] <- "MED_CTRL"#
#
i <- grep("MM", rna_id$STIMULANT)#
MM <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MM] <- "MUS_M1"#
#
i <- grep("TT", rna_id$STIMULANT)#
TT <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[TT] <- "TT"#
#
#
# need to calculate ddCt values by tube -- probably need to create loops
dim(pcr)
pcr
names(pcr)
levels(pcr$SAMPLEID)
pcr[6,]
range(subset(pcr, GENE == "RPL41")$Ct)
#
#
pcr <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/pcr.csv")#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# explore using product of housekeeping genes to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL X RPS", ylab="Tbet Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL X RPS", ylab="CD25 Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL X RPS", ylab="FOXP3 Ct")#
abline(v=600,lty=3)#
#
# read in document containing reference back to sample ID#
rna_id <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/rna_isolation.csv")#
rpl <- subset(pcr, GENE == "RPL41")#
rps <- subset(pcr, GENE == "RPS9")#
index1 <- match(rpl$SAMPLEID, rna_id$STORED.IN.TUBE)#
#
quartz(,8,4); layout(matrix(c(1,2),1,2))#
plot(rps$Ct, rna_id$PURITY[index1],xlim=c(15,35), xlab="Ct")#
points(rpl$Ct, rna_id$PURITY[index1],col=3)#
legend("topright", c("rps", "rpl"), pch=19,col=c(1,3))#
plot(rps$Ct, rna_id$CONCENTRATION[index1],xlim=c(15,35), ylim=c(0,50), xlab="Ct")#
points(rpl$Ct, rna_id$CONCENTRATION[index1],col=3)#
#
#
# explore using only RPL41 to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL", ylab="Tbet Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL", ylab="CD25 Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL", ylab="FOXP3 Ct")#
abline(v=25,lty=3)#
#
# use this to filter#
#
rpl <- subset(rpl, Ct <30)#
#
# ONLY THE TUBE ID'S FOR WHICH THE RPL41 CT WAS <30 WILL BE INCLUDED IN FURTHER ANALYSES#
#
index2 <- pcr$SAMPLEID %in% rpl$SAMPLEID#
#
pcr <- data.frame(SAMPLEID = pcr$SAMPLEID[index2], WELLID = pcr$WELL[index2], GENE = pcr$GENE[index2], Ct = pcr$Ct[index2], Exp = pcr$Exp[index2], stim = NA)
dim(pcr)
range(subset(pcr, GENE == "RPL41")$Ct)
pcr[6,]
#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# now need to work on analyses by stim, patient, visit#
#
i <- grep("MC", rna_id$STIMULANT)#
MC <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MC] <- "MED_CTRL"#
#
i <- grep("MM", rna_id$STIMULANT)#
MM <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MM] <- "MUS_M1"#
#
i <- grep("TT", rna_id$STIMULANT)#
TT <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[TT] <- "TT"
pcr[6,]
pcr[7,]
pcr[8,]
plot(subset(pcr, GENE == "Tbet")$Ct ~ subset(pcr, GENE == "Tbet")$stim)
plot(subset(pcr, GENE == "Tbet")$Ct ~ subset(pcr, GENE == "Tbet")$stim, na.rm = TRUE)
subset(pcr, GENE == "Tbet")$Ct
subset(pcr, GENE == "Tbet")$stim
range(subset(pcr, GENE == "Tbet")$stim)
range(subset(pcr, GENE == "Tbet")$Ct)
plot(subset(pcr, GENE == "Tbet")$Ct)
plot(subset(pcr, GENE == "Tbet")$Ct, subset(pcr, GENE == "Tbet")$stim)
plot(subset(pcr, GENE == "Tbet")$Ct ~ as.factor(subset(pcr, GENE == "Tbet")$stim))
plot(subset(pcr, GENE == "IL4")$Ct ~ as.factor(subset(pcr, GENE == "IL4")$stim))
plot(subset(pcr, GENE == "GATA3")$Ct ~ as.factor(subset(pcr, GENE == "GATA3")$stim))
plot(subset(pcr, GENE == "IFNg")$Ct ~ as.factor(subset(pcr, GENE == "IFNg")$stim))
subset(pcr, GENE == "IFNg")$Ct
pcr
subset(pcr, GENE == "INFg")$Ct
plot(subset(pcr, GENE == "INFg")$Ct ~ as.factor(subset(pcr, GENE == "INFg")$stim))
#
#
pcr <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/pcr.csv")#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# explore using product of housekeeping genes to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL X RPS", ylab="Tbet Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL X RPS", ylab="CD25 Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL X RPS", ylab="FOXP3 Ct")#
abline(v=600,lty=3)#
#
# read in document containing reference back to sample ID#
rna_id <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/rna_isolation.csv")#
rpl <- subset(pcr, GENE == "RPL41")#
rps <- subset(pcr, GENE == "RPS9")#
index1 <- match(rpl$SAMPLEID, rna_id$STORED.IN.TUBE)#
#
quartz(,8,4); layout(matrix(c(1,2),1,2))#
plot(rps$Ct, rna_id$PURITY[index1],xlim=c(15,35), xlab="Ct")#
points(rpl$Ct, rna_id$PURITY[index1],col=3)#
legend("topright", c("rps", "rpl"), pch=19,col=c(1,3))#
plot(rps$Ct, rna_id$CONCENTRATION[index1],xlim=c(15,35), ylim=c(0,50), xlab="Ct")#
points(rpl$Ct, rna_id$CONCENTRATION[index1],col=3)#
#
#
# explore using only RPL41 to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL", ylab="Tbet Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL", ylab="CD25 Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL", ylab="FOXP3 Ct")#
abline(v=25,lty=3)#
#
# use this to filter#
#
rpl <- subset(rpl, Ct <30)#
#
# ONLY THE TUBE ID'S FOR WHICH THE RPL41 CT WAS <30 WILL BE INCLUDED IN FURTHER ANALYSES#
#
index2 <- pcr$SAMPLEID %in% rpl$SAMPLEID#
#
pcr <- data.frame(SAMPLEID = pcr$SAMPLEID[index2], WELLID = pcr$WELL[index2], GENE = pcr$GENE[index2], Ct = pcr$Ct[index2], Exp = pcr$Exp[index2], stim = NA)#
#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# now need to work on analyses by stim, patient, visit#
#
i <- grep("MC", rna_id$STIMULANT)#
MC <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MC] <- "MED_CTRL"#
#
i <- grep("MM", rna_id$STIMULANT)#
MM <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MM] <- "MUS_M1"#
#
i <- grep("TT", rna_id$STIMULANT)#
TT <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[TT] <- "TT"#
#
#
# need to calculate ddCt values by tube -- probably need to create loops
quartz()
plot(subset(pcr, GENE == "GATA3")$Ct ~ as.factor(subset(pcr, GENE == "GATA3")$stim))
plot(subset(pcr, GENE == "IL10")$Ct ~ as.factor(subset(pcr, GENE == "IL10")$stim))
plot(subset(pcr, GENE == "FOXP3")$Ct ~ as.factor(subset(pcr, GENE == "FOXP3")$stim))
plot(subset(pcr, GENE == "CD25")$Ct ~ as.factor(subset(pcr, GENE == "CD25")$stim))
plot(subset(pcr, GENE == "RPS9")$Ct ~ as.factor(subset(pcr, GENE == "RPS9")$stim))
plot(subset(pcr, GENE == "IFNg")$Ct ~ as.factor(subset(pcr, GENE == "IFNg")$stim))
#
#
pcr <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/pcr.csv")#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# explore using product of housekeeping genes to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL X RPS", ylab="Tbet Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL X RPS", ylab="CD25 Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL X RPS", ylab="FOXP3 Ct")#
abline(v=600,lty=3)#
#
# read in document containing reference back to sample ID#
rna_id <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/rna_isolation.csv")#
rpl <- subset(pcr, GENE == "RPL41")#
rps <- subset(pcr, GENE == "RPS9")#
index1 <- match(rpl$SAMPLEID, rna_id$STORED.IN.TUBE)#
#
quartz(,8,4); layout(matrix(c(1,2),1,2))#
plot(rps$Ct, rna_id$PURITY[index1],xlim=c(15,35), xlab="Ct")#
points(rpl$Ct, rna_id$PURITY[index1],col=3)#
legend("topright", c("rps", "rpl"), pch=19,col=c(1,3))#
plot(rps$Ct, rna_id$CONCENTRATION[index1],xlim=c(15,35), ylim=c(0,50), xlab="Ct")#
points(rpl$Ct, rna_id$CONCENTRATION[index1],col=3)#
#
#
# explore using only RPL41 to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL", ylab="Tbet Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL", ylab="CD25 Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL", ylab="FOXP3 Ct")#
abline(v=25,lty=3)#
#
# use this to filter#
#
rpl <- subset(rpl, Ct <30)#
#
# ONLY THE TUBE ID'S FOR WHICH THE RPL41 CT WAS <30 WILL BE INCLUDED IN FURTHER ANALYSES#
#
index2 <- pcr$SAMPLEID %in% rpl$SAMPLEID#
#
pcr <- data.frame(SAMPLEID = pcr$SAMPLEID[index2], WELLID = pcr$WELL[index2], GENE = pcr$GENE[index2], Ct = pcr$Ct[index2], Exp = pcr$Exp[index2], stim = NA)#
#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# now need to work on analyses by stim, patient, visit#
#
i <- grep("MC", rna_id$STIMULANT)#
MC <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MC] <- "MED_CTRL"#
#
i <- grep("MM", rna_id$STIMULANT)#
MM <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MM] <- "MUS_M1"#
#
i <- grep("TT", rna_id$STIMULANT)#
TT <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[TT] <- "TT"#
#
i <- grep("LPS", rna_id$STIMULANT)#
LPS <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[LPS] <- "LPS"#
#
#
# need to calculate ddCt values by tube -- probably need to create loops
plot(subset(pcr, GENE == "LPS")$Ct ~ as.factor(subset(pcr, GENE == "LPS")$stim))
pcr
#
#
pcr <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/pcr.csv")#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# explore using product of housekeeping genes to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL X RPS", ylab="Tbet Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL X RPS", ylab="CD25 Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL X RPS", ylab="FOXP3 Ct")#
abline(v=600,lty=3)#
#
# read in document containing reference back to sample ID#
rna_id <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/rna_isolation.csv")#
rpl <- subset(pcr, GENE == "RPL41")#
rps <- subset(pcr, GENE == "RPS9")#
index1 <- match(rpl$SAMPLEID, rna_id$STORED.IN.TUBE)#
#
quartz(,8,4); layout(matrix(c(1,2),1,2))#
plot(rps$Ct, rna_id$PURITY[index1],xlim=c(15,35), xlab="Ct")#
points(rpl$Ct, rna_id$PURITY[index1],col=3)#
legend("topright", c("rps", "rpl"), pch=19,col=c(1,3))#
plot(rps$Ct, rna_id$CONCENTRATION[index1],xlim=c(15,35), ylim=c(0,50), xlab="Ct")#
points(rpl$Ct, rna_id$CONCENTRATION[index1],col=3)#
#
#
# explore using only RPL41 to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL", ylab="Tbet Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL", ylab="CD25 Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL", ylab="FOXP3 Ct")#
abline(v=25,lty=3)#
#
# use this to filter#
#
rpl <- subset(rpl, Ct <30)#
#
# ONLY THE TUBE ID'S FOR WHICH THE RPL41 CT WAS <30 WILL BE INCLUDED IN FURTHER ANALYSES#
#
index2 <- pcr$SAMPLEID %in% rpl$SAMPLEID#
#
pcr <- data.frame(SAMPLEID = pcr$SAMPLEID[index2], WELLID = pcr$WELL[index2], GENE = pcr$GENE[index2], Ct = pcr$Ct[index2], Exp = pcr$Exp[index2], stim = NA)#
#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# now need to work on analyses by stim, patient, visit#
#
i <- grep("MC", rna_id$STIMULANT)#
MC <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MC] <- "MED_CTRL"#
#
i <- grep("MM", rna_id$STIMULANT)#
MM <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MM] <- "MUS_M1"#
#
i <- grep("TT", rna_id$STIMULANT)#
TT <- pcr$SAMPLEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[TT] <- "TT"#
#
#
# need to calculate ddCt values by tube -- probably need to create loops
plot(subset(pcr, GENE == "IFNg")$Ct ~ as.factor(subset(pcr, GENE == "IFNg")$stim))
plot(subset(pcr, GENE == "GATA3")$Ct ~ as.factor(subset(pcr, GENE == "GATA3")$stim))
plot(subset(pcr, GENE == "RPS9")$Ct ~ as.factor(subset(pcr, GENE == "RPS9")$stim))
#
#
pcr <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/pcr.csv")#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# explore using product of housekeeping genes to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL X RPS", ylab="Tbet Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL X RPS", ylab="CD25 Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL X RPS", ylab="FOXP3 Ct")#
abline(v=600,lty=3)#
#
# read in document containing reference back to sample ID#
rna_id <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/rna_isolation.csv")#
rpl <- subset(pcr, GENE == "RPL41")#
rps <- subset(pcr, GENE == "RPS9")#
index1 <- match(rpl$SAMPLEID, rna_id$STORED.IN.TUBE)#
#
quartz(,8,4); layout(matrix(c(1,2),1,2))#
plot(rps$Ct, rna_id$PURITY[index1],xlim=c(15,35), xlab="Ct")#
points(rpl$Ct, rna_id$PURITY[index1],col=3)#
legend("topright", c("rps", "rpl"), pch=19,col=c(1,3))#
plot(rps$Ct, rna_id$CONCENTRATION[index1],xlim=c(15,35), ylim=c(0,50), xlab="Ct")#
points(rpl$Ct, rna_id$CONCENTRATION[index1],col=3)#
#
#
# explore using only RPL41 to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL", ylab="Tbet Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL", ylab="CD25 Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL", ylab="FOXP3 Ct")#
abline(v=25,lty=3)#
#
# use this to filter#
#
rpl <- subset(rpl, Ct <30)#
#
# ONLY THE TUBE ID'S FOR WHICH THE RPL41 CT WAS <30 WILL BE INCLUDED IN FURTHER ANALYSES#
#
index2 <- pcr$SAMPLEID %in% rpl$SAMPLEID#
#
pcr <- data.frame(TUBEID = pcr$SAMPLEID[index2], WELLID = pcr$WELL[index2], GENE = pcr$GENE[index2], Ct = pcr$Ct[index2], Exp = pcr$Exp[index2], stim = NA)#
#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# now need to work on analyses by stim, patient, visit#
#
i <- grep("MC", rna_id$STIMULANT)#
MC <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MC] <- "MED_CTRL"#
#
i <- grep("MM", rna_id$STIMULANT)#
MM <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MM] <- "MUS_M1"#
#
i <- grep("TT", rna_id$STIMULANT)#
TT <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[TT] <- "TT"#
#
#
# need to calculate ddCt values by tube -- probably need to create loops
pcr
rm(list=ls())
#
#
pcr <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/pcr.csv")#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# explore using product of housekeeping genes to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL X RPS", ylab="Tbet Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL X RPS", ylab="CD25 Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL X RPS", ylab="FOXP3 Ct")#
abline(v=600,lty=3)#
#
# read in document containing reference back to sample ID#
rna_id <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/rna_isolation.csv")#
rpl <- subset(pcr, GENE == "RPL41")#
rps <- subset(pcr, GENE == "RPS9")#
index1 <- match(rpl$SAMPLEID, rna_id$STORED.IN.TUBE)#
#
quartz(,8,4); layout(matrix(c(1,2),1,2))#
plot(rps$Ct, rna_id$PURITY[index1],xlim=c(15,35), xlab="Ct")#
points(rpl$Ct, rna_id$PURITY[index1],col=3)#
legend("topright", c("rps", "rpl"), pch=19,col=c(1,3))#
plot(rps$Ct, rna_id$CONCENTRATION[index1],xlim=c(15,35), ylim=c(0,50), xlab="Ct")#
points(rpl$Ct, rna_id$CONCENTRATION[index1],col=3)#
#
#
# explore using only RPL41 to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL", ylab="Tbet Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL", ylab="CD25 Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL", ylab="FOXP3 Ct")#
abline(v=25,lty=3)#
#
# use this to filter#
#
rpl <- subset(rpl, Ct <30)#
#
# ONLY THE TUBE ID'S FOR WHICH THE RPL41 CT WAS <30 WILL BE INCLUDED IN FURTHER ANALYSES#
#
index2 <- pcr$SAMPLEID %in% rpl$SAMPLEID#
#
pcr <- data.frame(SAMPLE = NA, TUBEID = pcr$SAMPLEID[index2], WELLID = pcr$WELL[index2], GENE = pcr$GENE[index2], Ct = pcr$Ct[index2], Exp = pcr$Exp[index2], stim = NA)#
#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# now need to work on analyses by stim, patient, visit#
#
i <- grep("MC", rna_id$STIMULANT)#
MC <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MC] <- "MED_CTRL"#
#
i <- grep("MM", rna_id$STIMULANT)#
MM <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MM] <- "MUS_M1"#
#
i <- grep("TT", rna_id$STIMULANT)#
TT <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[TT] <- "TT"#
#
#
# need to calculate ddCt values by tube -- probably need to create loops
pcr
length(levels(pcr$TUBEID))
subset(pcr, TUBEID == levels(pcr$TUBEID)[1])
levels(pcr$TUBEID)[1]
levels(pcr$TUBEID)[4]
subset(pcr, TUBEID == 1)
levels(pcr$TUBEID)
subset(pcr, TUBEID == "1")
subset(pcr, TUBEID == "115")
subset(pcr, TUBEID == "116")
subset(pcr, TUBEID == "NTC")
subset(pcr, TUBEID == "78")
subset(pcr, TUBEID == levels(pcr$TUBEID)[2])
temp <- subset(pcr, TUBEID == levels(pcr$TUBEID)[2])
length(temp)
temp <- subset(pcr, TUBEID == levels(pcr$TUBEID)[1])
length(temp)
temp
is.null(temp)
length(rows(temp))
dim(temp)[1]
dim(temp)[2]
temp <- subset(pcr, TUBEID == levels(pcr$TUBEID)[2])
temp
ls()
names(rna_id)
subset(rna_id, STORED.IN.TUBE == levels(pcr$TUBEID)[2])
subset(rna_id, STORED.IN.TUBE. == levels(pcr$TUBEID)[2])
subset(rna_id, STORED.IN.TUBE. == levels(pcr$TUBEID)[2])$SAMPLE.ID
temp
temp$SAMPLE <- subset(rna_id, STORED.IN.TUBE. == levels(pcr$TUBEID)[2])$SAMPLE.ID
temp$SAMPLE
temp
subset(pcr, TUBEID == levels(pcr$TUBEID)[2])
subset(pcr, TUBEID == levels(pcr$TUBEID)[2]) <- subset(rna_id, STORED.IN.TUBE. == levels(pcr$TUBEID)[2])$SAMPLE.ID
subset(pcr, TUBEID == levels(pcr$TUBEID)[2]) <- x
subset(pcr, TUBEID == levels(pcr$TUBEID)[2]) <- "x"
i <- grep(levels(pcr$TUBEID)[2], pcr$TUBEID)
i
pcr$SAMPLE[i]
pcr$SAMPLE[i] <- subset(rna_id, STORED.IN.TUBE. == levels(pcr$TUBEID)[2])$SAMPLE.ID
pcr$SAMPLE[i]
subset(rna_id, STORED.IN.TUBE. == levels(pcr$TUBEID)[2])$SAMPLE.ID
as.character(subset(rna_id, STORED.IN.TUBE. == levels(pcr$TUBEID)[2])$SAMPLE.ID)
pcr$SAMPLE[i] <- as.character(subset(rna_id, STORED.IN.TUBE. == levels(pcr$TUBEID)[2])$SAMPLE.ID)
pcr$SAMPLE[i]
#
#
pcr <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/pcr.csv")#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# explore using product of housekeeping genes to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL X RPS", ylab="Tbet Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL X RPS", ylab="CD25 Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL X RPS", ylab="FOXP3 Ct")#
abline(v=600,lty=3)#
#
# read in document containing reference back to sample ID#
rna_id <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/rna_isolation.csv")#
rpl <- subset(pcr, GENE == "RPL41")#
rps <- subset(pcr, GENE == "RPS9")#
index1 <- match(rpl$SAMPLEID, rna_id$STORED.IN.TUBE)#
#
quartz(,8,4); layout(matrix(c(1,2),1,2))#
plot(rps$Ct, rna_id$PURITY[index1],xlim=c(15,35), xlab="Ct")#
points(rpl$Ct, rna_id$PURITY[index1],col=3)#
legend("topright", c("rps", "rpl"), pch=19,col=c(1,3))#
plot(rps$Ct, rna_id$CONCENTRATION[index1],xlim=c(15,35), ylim=c(0,50), xlab="Ct")#
points(rpl$Ct, rna_id$CONCENTRATION[index1],col=3)#
#
#
# explore using only RPL41 to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL", ylab="Tbet Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL", ylab="CD25 Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL", ylab="FOXP3 Ct")#
abline(v=25,lty=3)#
#
# use this to filter#
#
rpl <- subset(rpl, Ct <30)#
#
# ONLY THE TUBE ID'S FOR WHICH THE RPL41 CT WAS <30 WILL BE INCLUDED IN FURTHER ANALYSES#
#
index2 <- pcr$SAMPLEID %in% rpl$SAMPLEID#
#
pcr <- data.frame(SAMPLE = NA, TUBEID = pcr$SAMPLEID[index2], WELLID = pcr$WELL[index2], GENE = pcr$GENE[index2], Ct = pcr$Ct[index2], Exp = pcr$Exp[index2], stim = NA, dCT = NA)#
#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# now need to work on analyses by stim, patient, visit#
#
i <- grep("MC", rna_id$STIMULANT)#
MC <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MC] <- "MED_CTRL"#
#
i <- grep("MM", rna_id$STIMULANT)#
MM <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MM] <- "MUS_M1"#
#
i <- grep("TT", rna_id$STIMULANT)#
TT <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[TT] <- "TT"#
#
#
# need to calculate dCt values by tube and grab sample id from rna_isolation file#
#
#
for (step in 1:length(levels(pcr$TUBEID))) {#
	w <- subset(pcr, TUBEID == levels(pcr$TUBEID)[step])#
	if (dim(w)[1] != 0) {#
		i <- grep(levels(pcr$TUBEID)[step], pcr$TUBEID)#
		pcr$SAMPLE[i] <- as.character(subset(rna_id, STORED.IN.TUBE. == levels(pcr$TUBEID)[step])$SAMPLE.ID)#
		}#
	#
	}
pcr
i
pcr[1,]
pcr[i,]
subset(pcr[i,], GENE == "RPL41")
subset(pcr[i,], GENE == "RPL41")$Ct
pcr[i,]$dCT = pcr[i,]$Ct - subset(pcr[i,], GENE == "RPL41")$Ct
pcr[i,]
rm(list=ls())
#
#
pcr <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/pcr.csv")#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# explore using product of housekeeping genes to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL X RPS", ylab="Tbet Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL X RPS", ylab="CD25 Ct")#
abline(v=600,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct*subset(pcr, GENE=="RPS9")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL X RPS", ylab="FOXP3 Ct")#
abline(v=600,lty=3)#
#
# read in document containing reference back to sample ID#
rna_id <- read.csv("/Users/Guest/Public/Shreff_lab/JAX/pcr_data/rna_isolation.csv")#
rpl <- subset(pcr, GENE == "RPL41")#
rps <- subset(pcr, GENE == "RPS9")#
index1 <- match(rpl$SAMPLEID, rna_id$STORED.IN.TUBE)#
#
quartz(,8,4); layout(matrix(c(1,2),1,2))#
plot(rps$Ct, rna_id$PURITY[index1],xlim=c(15,35), xlab="Ct")#
points(rpl$Ct, rna_id$PURITY[index1],col=3)#
legend("topright", c("rps", "rpl"), pch=19,col=c(1,3))#
plot(rps$Ct, rna_id$CONCENTRATION[index1],xlim=c(15,35), ylim=c(0,50), xlab="Ct")#
points(rpl$Ct, rna_id$CONCENTRATION[index1],col=3)#
#
#
# explore using only RPL41 to filter out poor quality data#
quartz(,12,4); layout(matrix(c(1:3),1,3))#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="Tbet")$Ct, xlab="RPL", ylab="Tbet Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="CD25")$Ct, xlab="RPL", ylab="CD25 Ct")#
abline(v=25,lty=3)#
plot(subset(pcr, GENE=="RPL41")$Ct, subset(pcr, GENE=="FOXP3")$Ct, xlab="RPL", ylab="FOXP3 Ct")#
abline(v=25,lty=3)#
#
# use this to filter#
#
rpl <- subset(rpl, Ct <30)#
#
# ONLY THE TUBE ID'S FOR WHICH THE RPL41 CT WAS <30 WILL BE INCLUDED IN FURTHER ANALYSES#
#
index2 <- pcr$SAMPLEID %in% rpl$SAMPLEID#
#
pcr <- data.frame(SAMPLE = NA, TUBEID = pcr$SAMPLEID[index2], WELLID = pcr$WELL[index2], GENE = pcr$GENE[index2], Ct = pcr$Ct[index2], Exp = pcr$Exp[index2], stim = NA, dCT = NA)#
#
genef <- factor(pcr$GENE)#
exp <- tapply(pcr$Ct, genef, fivenum)#
quartz(,8,4); boxplot(exp)#
#
# now need to work on analyses by stim, patient, visit#
#
i <- grep("MC", rna_id$STIMULANT)#
MC <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MC] <- "MED_CTRL"#
#
i <- grep("MM", rna_id$STIMULANT)#
MM <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[MM] <- "MUS_M1"#
#
i <- grep("TT", rna_id$STIMULANT)#
TT <- pcr$TUBEID %in% rna_id$STORED.IN.TUBE[i]#
pcr$stim[TT] <- "TT"#
#
#
# need to calculate dCt values by tube and grab sample id from rna_isolation file#
#
#
for (step in 1:length(levels(pcr$TUBEID))) {#
	w <- subset(pcr, TUBEID == levels(pcr$TUBEID)[step])#
	if (dim(w)[1] != 0) {#
		i <- grep(levels(pcr$TUBEID)[step], pcr$TUBEID)#
		pcr$SAMPLE[i] <- as.character(subset(rna_id, STORED.IN.TUBE. == levels(pcr$TUBEID)[step])$SAMPLE.ID)#
		# calculate dCt using RPL41#
		pcr[i,]$dCT = pcr[i,]$Ct - subset(pcr[i,], GENE == "RPL41")$Ct#
		}#
	}
names(pcr)
by(pcr$dCT, list(pcr$GENE, pcr$stim), fivenum)
sum <- by(pcr$dCT, list(pcr$GENE, pcr$stim), fivenum)
boxplot(sum)
sum <- by(pcr$dCT, list(pcr$stim,pcr$GENE), fivenum)
boxplot(sum)
sum
boxplot(log(sum))
levels(pcr$SAMPLE)
pcr
names(pcr)
levels(pcr$SAMPLE)
levels(as.factor(pcr$SAMPLE))
samplef <- as.factor(pcr$SAMPLE)
subset(pcr, SAMPLE == samplef[1])
subset(pcr, SAMPLE == samplef[2])
abline(c(3.5,6.5,9.5,12.5,15.5,18.5,21.5,24.5,27.5),lty=3)
abline(v=c(3.5,6.5,9.5,12.5,15.5,18.5,21.5,24.5,27.5),lty=3)
attributes(sum)
mtext(dimnames(sum)[[2]])
dimnames(sum)[[2]]
mtext(dimnames(sum)[[2]],at=c(2,5,8,11,14,17,20,23,26,29))
quartz(,10,2)
sum <- by(pcr$dCT, list(pcr$stim,pcr$GENE), fivenum)#
quartz(,10,4)#
#
boxplot(sum)#
abline(v=c(3.5,6.5,9.5,12.5,15.5,18.5,21.5,24.5,27.5),lty=3)#
mtext(dimnames(sum)[[2]],at=c(2,5,8,11,14,17,20,23,26,29))
